FindRear 😄

A tool to construct somatic rearrangements

Requirement

• python (>3.7)
• numpy
• pandas
• matplotlib
• argparse

A. Input file

Input_SV_file (6 columns about one SV are required)

1. SN: sample name
2. chr_1: the chromosome of low-end breakpoint
3. pos_1: genomic position of low-end breakpoint
4. flag_1: the orientation of low-end breakpoint
5. chr_2: the chromosome of low-end breakpoint
6. pos_2: genomic position of low-end breakpoint
7. flag_2: the orientation of low-end breakpoint

Input_bp/kb list (two columns are required)

1. sn: sample name that is consistent with sample name in input_SV_file
2. link: the bp/kb path

bp/kb file (normalized coverage of windows (200-bp or 10kbp))

1. bp_file: the normalized coverage of non-overlapping windows (200bp)

2. kp_file: the normalized coverage of non-overlapping windows (10kbp)
   

   *note:

   a. normalzied coverage is obtained from PATCHWORK results;

   b. the shape of bp/kp matrix is N and M (N = the number of SV breakpoints; M = 201, 100 windows on the either left or right side of breakpoint)

optional: --type

1. -type: choose the complex SV type you want to identify, consisting of complex TD/DEL, fold and unbalanced inversions.

B. identify rearrangements (example)

a. identify fold-back inversion

python  ../construct_rearrangements.py --type fold-back test.sv test.out bp.list kp.list

b. identify unbalnced inversions

python  ../construct_rearrangements.py --type inv test.sv test.out bp.list kp.list

c. identify TD-del rearrangements

python ../construct_rearrangements.py --type td-del test.sv test.out bp.list kp.list